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Clinical Science

Brief Report: The Impact of Disease Stage on Early Gaps in ART in the “Treatment for All” Era—A Multisite Cohort Study

Katz, Ingrid T. MD, MHSca,b,c; Musinguzi, Nicholas MScd; Bell, Kathleen MPHe; Cross, Anna MBChBf; Bwana, Mwebesa B. MBChB, MPHd; Amanyire, Gideon MBChB, MPHd; Asiimwe, Stephen MD, MPH, DrPHd,g; Orrell, Catherine MBChB, MMed, MScf; Bangsberg, David R. MSc, MD, MPHh; Haberer, Jessica E. MDb,e, On Behalf of the META (Measuring Early Treatment Adherence) Team Investigators

Author Information
JAIDS Journal of Acquired Immune Deficiency Syndromes: April 15, 2021 - Volume 86 - Issue 5 - p 562-567
doi: 10.1097/QAI.0000000000002605
  • Open

Abstract

BACKGROUND

The widespread availability of antiretroviral therapy (ART) throughout sub-Saharan Africa has transformed the HIV epidemic across the region, increasing the number of people on treatment from 100,000 in 2004 to 15.4 million in 2017.1 This increase in availability has dramatically impacted cumulative ART initiation, with some regions experiencing up to a 17.6 percentage point increase from 6–18 months pre-expansion to 6–18 months postexpansion.2 After the adoption of national treat-all policies in 6 sub-Saharan African nations, statistically significant increases in rapid ART initiation were observed in 4 countries, with sustained or amplified improvements in adherence.3

In South Africa, 70.6% of the 7.9 million people living with HIV (PLWH) ages 15–64 are currently on treatment, with 87.5% of those on treatment virally suppressed.4 This represents a 2-fold increase in the past decade,5 accelerated by the expansion in ART eligibility to Treat All as of September 2016.6 In Uganda, where the treatment guidelines were expanded to Treat All as of November 2016,3 treatment initiation numbers are similar with for PLWH ages 15–64 with estimates of 89.3% of PLWH on ART and of which 90.6% are virally suppressed.7

Although there are data to suggest the impact of guideline expansions has increased early ART initiation in sub-Saharan Africa,2,3 early gaps in treatment (ie, discontinuation of ≥30 days within the first 6 months) persist.6 The first 6 months of treatment after initiation are crucial to long-term adherence and immunological and virologic success, with 6-month CD4 count and viral load being the 2 most important factors in prediction of progression to AIDS or death.8 Because of the clinical significance of this period, more information is needed to understand why treatment discontinuation continues at this vulnerable stage in care.

We leveraged a prospective observational cohort study of individuals initiating ART at early-stage versus late-stage disease to understand how disease stage impacts early gaps in treatment in 2 countries in the region—South Africa and Uganda. The data collected during this observational cohort study allowed for an in-depth investigation into sociobehavioral factors that could affect health decision-making, care access, and treatment-related behavior beyond the health status. We identified clinical and psychosocial predictors of gaps in these 2 groups and hypothesized that individuals starting ART with late-stage disease have faced long-term marginalization and challenges in coping with their HIV diagnosis and, therefore, would be more likely to halt treatment. We based this hypothesis on the literature that suggests that patients who present late to care are less likely to remain in care.9,10

METHODS

Study Design and Setting

This analysis used data from the Monitoring Early Treatment Adherence (META) Study (NCT02419066), a prospective, observational study designed to assess ART adherence among 2 cohorts of men and women initiating ART in routine care in Cape Town, South Africa, and southwestern Uganda. Full protocol details have been published previously.11 Our previous study found that one cohort initiated treatment with early-stage HIV infection (CD4 > 350 cells/mL) and one initiated with late-stage HIV infection (CD4 < 200 cells/mL). Participants were seen at 0, 6, and 12 months for administration of sociobehavioral questionnaires and HIV-1 RNA levels. Adherence was monitored electronically in real-time (Wisepill wireless adherence device; Wisepill Technologies, South Africa). The parent study showed that adherence data varied by site. Given this, we chose to analyze data from each site separately. In Uganda, adherence over 12 months was not significantly different between individuals with early-stage and late-stage initiation, with an overall median of 89%. In South Africa, median adherence rates over 12 months were 77% and 52%, respectively.11

Analysis

For this analysis, early gaps in ART were defined as ≥30 consecutive days without evidence of adherence in the first 6 months of treatment among all individuals initiating ART. Our previous study looked at ≥7 days as a measure of viremia. We chose to look at ≥30 consecutive days as a measure of lack of care engagement which is comparable with previous studies.12–15 Demographic and clinical factors at baseline (chosen after being identified in the previous literature as potential factors of treatment initiation16 and adherence17) were compared across groups using χ2 for categorical and Wilcoxon rank sum test for continuous factors to identify potentially confounding covariates. Pregnant women were not included in this analysis because factors influencing care often differ substantially from nonpregnant individuals.18 Logistic regression models were used to estimate predictors of early gaps in ART usage.

In determining what variables to retain for the multivariable model, for each potential confounder, we fit a univariable model including the confounder alongside the study cohort and retained in the multivariable models all potential confounders with a significance level of P < 0.10. To distinguish nonuse of the adherence monitor versus true nonadherence during the recorded gap, we assessed the relationship between gaps and the 6-month viremia using χ2 tests. The Uganda and South Africa sites were analyzed separately because of numerous demographic and socioeconomic differences between them. Adjusted analyses were restricted to South Africa, given the limited numbers of participants with early gaps in Uganda.

Ethical Considerations

Study procedures were approved by Ethical and Regulatory Committees at Partners Healthcare (Protocol P2014P002620), the Mbarara University of Science and Technology (Protocol 11/04–14), Uganda National Council for Science and Technology (Protocol HS 1667), University of Cape Town (Protocol 797/2014), and Western Cape province (Protocol WC2014_RP16_343) in South Africa. All participants provided written informed consent.

RESULTS

Participant Characteristics

Of the 904 people living with HIV enrolled in the META study between March 2015 and September 2016, 421 were in South Africa, and 483 were in Uganda. In total, adherence data were available at 6 months for 96% (n = 868); 77% (n = 669) were found eligible for this analysis, with 199 participants excluded because of pregnancy. The median age of analyzed participants was 33 years; approximately, 60% were female, and the study site was divided approximately 48%–52% between South Africa and Uganda (Table 1).

TABLE 1. - Participant Demographics and Outcomes by the Site
Variable Uganda
N (%) or Median (IQR)
N = 347
South Africa
N (%) or Median (IQR)
N = 322
P
Sociodemographic characteristics (baseline)
 Cohort 0.19
  Early-stage disease 175 (50) 146 (45)
  Late-stage disease 172 (50) 176 (55)
 Female 198 (57) 204 (63) 0.10
 Age 31 (26–39) 35 (29–42) <0.001
 Married 159 (46) 63 (20) <0.001
 Sexually active in the past 6 mo 267 (77) 280 (88) 0.001
 Completed high-school education 193 (56) 274 (85) <0.001
 Literate in English or local language 295 (85) 303 (96) <0.001
 Employed 308 (89) 148 (46) <0.001
 Forced sex 29 (8) 13 (4) 0.02
 Annual income (USD) 333 (74–740) 728 (0–2821) <0.001
 Structural barrier score 0 (0–3) 12 (8–18) <0.001
 Clinic “too far” 56 (16) 100 (31) <0.001
 Severe food insecurity 110 (32) 217 (67) <0.001
 Social support score (instrumental) 31 (23–40) 29 (21–41) 0.58
 Social support score (emotional) 36 (25–44) 30 (21–43) 0.013
 Stigma (perceived negative attitudes) 1 (0–3) 3 (1–4) <0.001
 Stigma (disclosure concerns) 3 (1–5) 3 (1–6) 0.78
 Disclosed to anybody 289 (83) 266 (83) 0.75
 Coping score 2.3 (2.0–2.4) 2.3 (2.3–2.6) <0.001
 Medical mistrust score 2 (1–2.5) 2 (2–2.5) <0.001
 Satisfaction score 3.5 (3.2–4) 3.0 (2.8–3.3) <0.001
 Physical health score 39 (36–43) 41 (36–47) <0.001
 Mental health score 47 (36–60) 37 (32–46) <0.001
 Probable depression 88 (25) 158 (49) <0.001
 Heavy alcohol usage 33 (10) 96 (30) <0.001
 First HIV test ≥30 days prior to enrolment 177 (51) 175 (60) 0.021
 Other medications beside ART 286 (82) 75 (23) <0.001
Outcomes
 Presence of 30-day interruptions 21 (6) 70 (22) <0.001
 Time (days) to interruption 87 (74–105) 77 (43–101) 0.14
 6-month viral suppression 307 (89) 256 (80) 0.002

Early Gaps in Treatment

Ninety-one individuals (14%) showed early gaps in ART use, 70 individuals from South Africa and 21 individuals from Uganda, with a median time from ART initiation to treatment gap of 77 days [interquartile range (IQR): 43–101] and 87 days (IQR: 74–105), respectively. The median duration of adherence gaps was 48 days (IQR: 36–56) among Ugandan participants and 45 days (IQR: 38–65) among South African participants. The proportion of early-ART and late-ART initiators with treatment gaps was 9.7% and 17.2%, respectively (P = 0.004). Although 71 (78%) of those with early gaps across sites ultimately resumed care, they were still more likely to have detectable viremia at month 6 (P ≤ 0.01). Among people who did not have a gap in treatment, 87.5% were virally suppressed versus 66.0% among those who had a gap in care (P < 0.001). Almost all participant sociodemographic characteristics differed across the 2 sites with a few exceptions (Table 1). In general, South African participants were older, were more likely to be depressed, more likely to be heavy alcohol consumers, and had a higher physical but lower mental health score.

Multivariable regression modeling was restricted to South Africa, given the limited numbers of early gaps among participants in Uganda. The multivariable model results are shown in Table 2. In the adjusted model, we found that secondary education and higher physical health score provided a protective effect against early gaps [(aOR 0.4, 95% CI: 0.2 to 0.8) and (aOR 0.93, 95% CI: 0.9 to 1.0), respectively]. Participants reporting the clinic to be too far had double the odds of early gaps (aOR 2.2: 95% CI: 1.2 to 4.1). There was no significant difference across early-stage versus late-stage disease, age, gender, marital status, or employment, despite the significant difference in overall adherence.

TABLE 2. - Adjusted Analyses of Factors Associated With Early Gaps in ART Among South African Participants Living With HIV
Variable Univariable Model Multivariable Model
aOR 95% CI P aOR 95% CI P
Cohort
 Late-stage vs. early-stage disease 1.80 1.03 to 3.13 0.037 1.46 0.78 to 2.73 0.243
Age (5 year effect) 1.06 0.93 to 1.20 0.391
Female 1.18 0.67 to 2.09 0.560
Sexually active in the past 6 mo 0.82 0.38 to 1.76 0.605
Completed high-school education
 Completed vs. never completed high school 3.00 0.16 to 0.57 <0.001 0.33 0.16 to 0.67 0.002
Literate in English or local language 0.24 0.08 to 0.69 0.008 0.323
Employed 0.77 0.45 to 1.32 0.336
Forced sex 0.71 0.15 to 3.31 0.660
Annual income (per 100 USD) 0.99 0.98 to 1.01 0.318
Structural barrier score 1.03 0.99 to 1.07 0.200
Married or living together 0.55 0.25 to 1.18 0.124 0.43 0.18 to 1.01 0.053
Clinic “too far” 1.93 1.12 to 3.35 0.019 2.28 1.25 to 4.15 0.009
Physical health score 0.93 0.89 to 0.97 <0.001 0.93 0.89 to 0.97 0.001
Mental health score 1.00 0.97 to 1.03 0.996
Social support score (instrumental) 0.99 0.96 to 1.02 0.464
Social support score (emotional) 0.99 0.97 to 1.02 0.581
Stigma (perceived negative attitudes) 1.04 0.89 to 1.20 0.630
Stigma (disclosure concerns) 0.99 0.88 to 1.10 0.818
Disclosed to anybody 0.94 0.46 to 1.92 0.864
Coping score 1.15 0.73 to 1.82 0.554
Medical mistrust score 1.02 0.62 to 1.67 0.948
Satisfaction score 1.22 0.69 to 2.18 0.491
Probable depression 1.36 0.79 to 2.32 0.270
Heavy alcohol usage 0.83 0.46 to 1.51 0.550
Other medications beside ART 1.47 0.80 to 2.68 0.21

DISCUSSION

Despite many successes in the global efforts to promote early and enduring treatment, early gaps in ART persist, resulting in higher odds of detectable viremia. These gaps remain significant for key vulnerable populations, particularly in South Africa, where we found 22% (70 of 322 participants) had an early gap in care, compared with 6% in Uganda. Although 71 (78%) of those with early gaps ultimately resumed care, having an early gap was still significantly associated with detectable viremia at 6 months. This finding is consistent with previous studies showing individuals in South Africa seem to be at a particular risk of early losses in care, with rates of loss as high as 25% in the first 6 months on treatment,6,19–21 preventing people living with HIV from achieving the long-term benefits of treatment. In this study, early gaps did not significantly differ between disease stage, suggesting that perception of health may contribute more than actual disease severity.

We originally hypothesized that individuals starting ART with late-stage disease have faced long-term marginalization and challenges in coping with their HIV diagnosis and, therefore, would be more likely to halt treatment. This hypothesis was based on our prior research22 showing ART-related decision-making is best understood within the larger context of risk perception, which posits that people make decisions about risks based on affect, stigma, and/or fear, and are highly loss averse.23 Although we did not find that disclosure/stigma were significantly associated with early losses, our findings may reflect a more nuanced interpretation of stigma. Our recent findings in another study in South Africa shows that internalized stigma may naturally decrease over time after an HIV diagnosis, whether someone is on treatment or not, because there is time to adjust to a diagnosis and acquire social support.24 Although we were unable to fully explore the impact of actual time to diagnosis on decision-making, this is an area that would benefit from future research.

In addition, those at a highest risk of early gaps in ART in South Africa appeared to be PLWH who reported that the clinic was “too far.” This finding is consistent with prior research in South Africa showing people living with HIV who struggle to remain in care often describe clinics as being hard to access and additionally may view health centers as stigmatizing and unwelcoming.16,25,26 Additional studies support our findings, citing poor testing accessibility, difficulties coordinating ART care, and pervasive stigma as contributing factors for risk of early gaps in ART.27,28

Ultimately, early losses impede the South African Government's ability to achieve population reductions in HIV by undermining the potential of the Prevention Access Campaign's Undetectable = Untransmittable (U = U) initiative.29 Beyond the implications for increased viral transmission, PLWH who drop out of care have high rates of mortality; 46% who drop out of public ART programs in sub-Saharan Africa ultimately succumb to the virus.30 The current national guidelines in South Africa require frequent client interaction with a health system that many find stigmatizing and located too far for easy access, with monthly clinical visits in the first 6 months after ART initiation. For those who drop out, the standard of care provides a clinic-initiated phone call and encouragement to re-establish care, but data from Khayelitsha township in the Western Cape show that this is insufficient for re-engagement.31

Given the multifactorial challenges that PLWH in South Africa face early in their care, differentiated service delivery models that use client-centered approaches to simplify and adapt services to reflect the preferences and needs of PLWH have the potential to improve retention in care for PLWH in South Africa.32,33 These differentiated care models are in line with the World Health Organization (WHO),34 the International AIDS Society guidelines,35 and the South African National Strategic Plan's consolidated guidelines36 and may remove some of the barriers identified in this study such as distance and education, by providing care within the community and supporting individuals with clinical navigation.37,38 Beyond providing flexible, client-centered care models, PLWH may benefit from interventions designed to promote resilience resources, focused on decreasing maladaptive coping strategies (eg, denial),39 promote new coping skills, improve social support, and reduce stigma for PLWH.40

Although this study provides valuable information about the sociobehavioral factors associated with early gaps in ART, it also presents a few key limitations. First, we recognize that the study was observational in nature, and therefore, the results of this study are limited to association, not causation. In addition, adherence monitoring may have influenced behavior. In addition, device nonuse may account for some nonadherence. As such, experiences may vary in the future and with long-term ART use. We had limited ability to comment on early gaps in Uganda, given the limited numbers of early gaps among individuals there, demonstrating that many PLWH in Uganda are successful in adhering to treatment early. We also did not measure drug resistance, which may have contributed to the presence of viremia among participants in this study.

In summary, this study allowed for in depth investigation of the sociobehavioral factors that contribute to early gaps in ART for PLWH in South Africa and Uganda. We found that the study population in South Africa had a higher rate of early gaps in ART compared with the population in Uganda. Among participants in South Africa, education, physical health, and perception of the clinic as “too far” were significantly associated with early gaps in ART. These findings can help inform future interventions that promote adherence to ART for this population.

ACKNOWLEDGMENTS

The authors dedicate this article to our dear colleague, Dr. Mwebesa Bosco Bwana, who departed this earth too soon. The authors are grateful for his contributions to this article, his leadership at the Mbarara University of Science and Technology and the Mbarara Regional Referral Hospital, and his many accomplishments as a physician scientist. The authors thank the individuals who participated in this study and the broader study team.

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Keywords:

HIV; early gaps; South Africa; Uganda

Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc.